EcoDes-DK15 v1.1.0 Teaser Dataset (Husby Klit)

<strong>!!! This is a teaser version of the data set (5MB) for the Husby Klit area !!!</strong><br> For the full data set see: https://doi.org/10.5281/zenodo.4756556 ------------------------------------------------------------------------------------------------------------------------------------------------ <strong>Seventy high-resolution ecological descriptors of vegetation and terrain for Denmark "EcoDes-DK15"</strong> The data are derived from the nationwide airborne laser scanning / LiDAR campaign of Denmark from 2014-2015 provided by the Danish Agency for Data Supply and Efficiency. <strong>Update: EcoDes-DK15 v1.1.0 (4 Dec. 2021)</strong> Following the recommendations and feedback during the first round of peer-review, we updated the EcoDes-DK processing pipeline and EcoDes-DK15 data set. The key changes are: New version of the source data optimised to contain only point data collected before the end of 2015. The source data for EcoDes-DK15 v1.0.0 unintentionally contained data from 2018. The new source data is documented here. New "date_stamp_*" auxiliary variables that illustrate the survey dates for the vegetation points in each cell. See updated descriptor documentation here. Re-scaling of "solar_radiation" variable to MJ per 100 m² per year. <strong>Detailed documentation for the data set can be found in the accompanying manuscript and GitHub repository:</strong> Assmann, J. J., Moeslund, J. E., Treier, U. A., and Normand, S.: EcoDes-DK15: High-resolution ecological descriptors of vegetation and terrain derived from Denmark's national airborne laser scanning data set, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2021-222, in review, 2021<strong><em>.</em></strong> https://github.com/jakobjassmann/ecodes-dk-lidar Files are compressed using bzip2 and tar archiving. The compressed archives can be extracted using commonly available archiving tools (for example 7z on Windows, the archiving tool on macOS and bz2 on Linux). A small example "teaser" subset (5 MB) of the data set, covering the Husby Klit area from Figure 7 in the manuscript, can be found here. <strong>Abstract (from manuscript)</strong> Biodiversity studies could strongly benefit from three-dimensional data on ecosystem structure derived from contemporary remote sensing technologies, such as Light Detection and Ranging (LiDAR). Despite the increasing availability of such data at regional and national scales, the average ecologist has been limited in accessing them due to high requirements on computing power and remote-sensing knowledge. We processed Denmark’s publicly available national Airborne Laser Scanning (ALS) data set acquired in 2014/15 together with the accompanying elevation model to compute 70 rasterized descriptors of interest for ecological studies. With a grain size of 10 m, these data products provide a snapshot of high-resolution measures including vegetation height, structure and density, as well as topographic descriptors including elevation, aspect, slope and wetness across more than forty thousand square kilometres covering almost all of Denmark’s terrestrial surface. The resulting data set is comparatively small (~94 GB, compressed 16.8 GB) and the raster data can be readily integrated into analytical workflows in software familiar to many ecologists (GIS software, R, Python). Source code and documentation for the processing workflow are openly available via a code repository, allowing for transfer to other ALS data sets, as well as modification or re-calculation of future instances of Denmark’s national ALS data set. We hope that our high-resolution ecological vegetation and terrain descriptors (EcoDes-DK15) will serve as an inspiration for the publication of further such data sets covering other countries and regions and that our rasterized data set will provide a baseline of the ecosystem structure for current and future studies of biodiversity, within Denmark and beyond. <strong>Acknowledgements (from manuscript)</strong> We would like to thank Andràs Zlinszky for his contributions to earlier versions of the data set, Charles Davison for feedback regarding data use and handling, as well as Matthew Barbee and Zsófia Koma for sharing their insights on the source data merger and Zsófia’s script to generate summary statistics for the different versions of the DHM point clouds. Funding for this work was provided by the Carlsberg Foundation (Distinguished Associate Professor Fellowships) and Aarhus University Research Foundation (AUFF-E-2015-FLS-8-73) to Signe Normand (SN). This work is a contribution to SustainScapes – Center for Sustainable Landscapes under Global Change (grant NNF20OC0059595 to SN).<strong>!!! 本文件为Husby Klit区域数据集的预览版（5 MB）!!!</strong><br>完整数据集请访问：https://doi.org/10.5281/zenodo.4756556<br>------------------------------------------------------------------------------------------------------------------------------------------------<br><strong>丹麦植被与地形70项高分辨率生态描述符数据集"EcoDes-DK15"</strong><br>本数据集源自丹麦数据供给与效率署（Danish Agency for Data Supply and Efficiency）提供的2014-2015年全国机载激光扫描/激光雷达（Light Detection and Ranging，LiDAR）观测项目。<br><strong>更新说明：EcoDes-DK15 v1.1.0（2021年12月4日）</strong><br>基于首轮同行评议的建议与反馈，我们更新了EcoDes-DK数据处理流程与EcoDes-DK15数据集。主要更新内容如下：<br>1. 优化后的新版源数据仅包含2015年末前采集的点云数据。EcoDes-DK15 v1.0.0的源数据意外混入了2018年的观测数据，新版源数据的相关说明已公开。<br>2. 新增`date_stamp_*`辅助变量，用于标注每个栅格单元内植被点云的观测日期。更新后的描述符文档可在此查阅。<br>3. 将`solar_radiation`（太阳辐射）变量的单位重新校准为兆焦/每100平方米²·年。<br><strong>本数据集的详细说明可参阅配套论文与GitHub代码仓库：</strong><br>Assmann, J. J., Moeslund, J. E., Treier, U. A. 与Normand, S.：《EcoDes-DK15：源自丹麦全国机载激光扫描数据集的植被与地形高分辨率生态描述符》，Earth Syst. Sci. Data Discuss. [预印本]，https://doi.org/10.5194/essd-2021-222，已投稿待审，2021<em>.</em><br>代码仓库地址：https://github.com/jakobjassmann/ecodes-dk-lidar<br>数据集文件采用bzip2与tar格式打包压缩，可通过通用解压工具（如Windows平台的7z、macOS自带归档工具、Linux平台的bz2工具）进行解压缩。<br>本数据集附带一份小型演示子集（5 MB），覆盖论文图7中的Husby Klit区域，可在此获取。<br><strong>论文摘要（节选自原文）</strong><br>生物多样性研究可从当代遥感技术（如激光雷达（Light Detection and Ranging，LiDAR））获取的生态系统结构三维数据中获益良多。尽管此类区域及国家级尺度的遥感数据日益丰富，但普通生态学者因对计算能力与遥感专业知识的较高要求，仍难以获取并使用这些数据。我们基于丹麦公开的2014/2015年全国机载激光扫描（Airborne Laser Scanning，ALS）数据集及配套高程模型，计算得到70项适用于生态研究的栅格化生态描述符。该数据集的栅格粒度为10米，覆盖丹麦近全部陆地表面（逾4万平方千米），提供了高分辨率的植被高度、结构与密度，以及高程、坡向、坡度、湿度等地表地形描述符的快照式数据。最终生成的数据集体量相对可控（未压缩约94 GB，压缩后约16.8 GB），且栅格数据可直接集成至多数生态学者熟悉的分析工作流中，如GIS软件、R语言与Python环境。数据处理流程的源代码与说明文档已通过代码仓库公开，可直接迁移至其他机载激光扫描数据集，也可针对丹麦未来的全国ALS数据集进行修改或重新计算。我们期望本高分辨率植被与地形生态描述符数据集（EcoDes-DK15）能够推动其他国家与地区同类数据集的公开出版，并为丹麦境内外当前及未来的生物多样性研究提供生态系统结构的基准数据。<br><strong>致谢（节选自原文）</strong><br>我们谨致谢忱：Andràs Zlinszky为本数据集早期版本作出的贡献，Charles Davison针对数据使用与处理提供的反馈，以及Matthew Barbee与Zsófia Koma分享的源数据合并思路，还有Zsófia编写的用于生成DHM点云不同版本统计量的脚本。本研究的经费由嘉士伯基金会（Distinguished Associate Professor Fellowships项目）与奥胡斯大学研究基金会（项目编号AUFF-E-2015-FLS-8-73）提供给Signe Normand（SN）。本研究隶属于全球变化下可持续景观中心SustainScapes，该中心由NNF20OC0059595项目资助给SN。